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• Botensilimab, an Fc-enhanced Anti-CTLA-4 Antibody, is Effective Against Tumors Poorly Responsive to Conventional Immunotherapy

  This study explores the genomic landscape associated with a novel Fc-engineered anti-CTLA-4 antibody (botensilimab) in advanced solid tumors. We seek to understand if enhancing the Fc-region affinity of anti-CTLA-4 antibodies can improve anti-tumor efficacy and expand clinical benefit to tumors poorly responsive to conventional immunotherapy. As part of an ongoing open-label, Phase 1, multicenter study, we conducted an exploratory sub-analysis of genomics data. The primary study evaluates the safety, tolerability, pharmacokinetics, and pharmacodynamics of botensilimab monotherapy and in combination with an anti-PD-1 antibody (balstilimab) in participants with advanced solid tumors. RNA from formalin-fixed paraffin-embedded (FFPE) tumor biopsies and matched normal blood samples were isolated and subjected to RNA-sequencing using the Personalis ImmunoID NeXT Platform. We demonstrated that anti-CTLA-4 engineered for enhanced FcγR affinity leverages FcγR-dependent mechanisms to potentiate T cell responsiveness, reduce intratumoral Tregs, and enhance antigen presenting cell activation. This genomic analysis contributes to our understanding of the molecular mechanisms underlying patient responses to Fc-engineered anti-CTLA-4 therapy and may inform future strategies to expand the clinical benefit of immune checkpoint blockade in cancer immunotherapy.

  Study phs003704

• Fgl2 Regulates FcγRIIB+ CD8+ T Cell Responses during Infection

  While the inhibitory receptor FcγRIIB has been shown to be upregulated on activated CD8+ T cells in both mice and humans, its impact on T cell fate during infection has not been fully elucidated. We identified an increase in FcγRIIB-expressing CD8+ T cells in COVID patients relative to healthy controls, and in mouse models of viral infection. Despite its well-known role as an Fc receptor, FcγRIIB also ligates the immunosuppressive cytokine Fgl2, resulting in CD8+ T cell apoptosis. Both chronic LCMV infection in mice and COVID in humans resulted in a significant increase in plasma Fgl2. Further, plasma Fgl2 was directly proportional to CD8+ T cell lymphopenia in COVID patients. To further understand the association of Fgl2 and CD8+ T cell lymphopenia following COVID infection, we assessed the transcriptomic profiles of PBMCs with high (≥ 9.153 ng/ml) vs low (defined as

  Study phs003870

• Data Access Committee KCL FC

  Dac EGAC00001000386

• Cookies

  Cookies https://ega-archive.org does not identify users on this site. It does use cookies, though. What is a cookie? Cookies are text files containing small amounts of information which are downloaded to your device when you visit a website. They allow a website to remember your preferences and are therefore useful to improve your online experience. Find out more information about cookies. Types of cookies we use Functional These cookies record the columns you wish to display or hide in the results page.Performance These cookies are used to analyse trends, administer the website, track visitor movements and gather broad demographic information for aggregate use. We use the information to compile reports and to help us improve our websites. These cookies are not linked to personally identifiable information. Session cookie A session cookie for a website only exists whilst the user is reading or navigating the website. When the user closes their web browser these cookies are usually removed.

  Documentation cookies

• MCF10A 12h IL6 classical signaling

  Gene expression after cell culture, 12h IL6+sgp130-Fc stimulated

  Dataset EGAD00010001970

• MCF10A 24h IL6 classical signaling

  Gene expression after cell culture, 24h IL6+sgp130-Fc stimulated

  Dataset EGAD00010001963

• Myeloma WGS

  Most patients with multiple myeloma (MM) die from progressive disease after relapse. To advance our understanding of MM evolution mechanisms, we performed whole-genome sequencing of 80 tumour-normal newly diagnosed pairs and 24 matched relapse tumours from the Myeloma XI trial.

  Study EGAS00001004000

• Characterization of a human iPSC-derived endocrine pancreas model

  Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. "insulin secretion"; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

  Study EGAS00001001803

• Anti-TIGIT antibody tiragolumab improves PD-L1 blockade via myeloid and Treg cells

  Tiragolumab, an anti-TIGIT antibody with an active IgG1/kappa Fc, demonstrated improved outcomes in the phase 2 CITYSCAPE trial (NCT03563716) when combined with atezolizumab (anti-PD-L1) versus atezolizumab alone1. However, there remains little consensus on the mechanism(s) of response with this combination2. We found that high baseline intratumoral macrophages and Tregs were associated with better outcomes in patients treated with atezolizumab plus tiragolumab but not with atezolizumab alone. Serum sample analysis revealed that macrophage activation was associated with clinical benefit in patients receiving the combination treatment. In mouse tumor models, tiragolumab surrogate antibodies inflamed tumor-associated macrophages, monocytes, and dendritic cells through Fc gamma receptors (FcɣR), in turn driving anti-tumor CD8+ T cells from an exhausted effector-like state to a more memory-like one. These results uncover a mechanism of action by which TIGIT checkpoint inhibitors can remodel immunosuppressive tumor microenvironments, and suggest that FcɣR engagement is an important consideration in anti-TIGIT antibody development.

  Study EGAS50000000251

• Expression profiling of a human endocrine pancreas iPSC model

  Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to the endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. “insulin secretion”; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

  Dataset EGAD00001002148

• Ribo-depleted RNA-sequencing of II.3, III.1, and III.3

  This datasets contains the Ribo-depleted RNA-sequencing of patients II.3, III.1, and III.3. Libraries were sequenced to a minimum depth of 195 million read pairs (2x75nts) on an Illumina NextSeq500 Midoutput FC.

  Dataset EGAD50000002364

• Mutational Landscape of MCPyV-Positive and MCPyV-Negative Merkel Cell Carcinomas

  Merkel cell carcinoma (MCC) is an aggressive neuroendocrine carcinoma of the skin most commonly found on the sun-exposed skin of older Caucasian adults. Roughly one-third of patients with MCCs die of the disease; therefore, MCC is the most lethal skin cancer on a case-by-case basis. 49 cases were studied, and putative cancer driver gene mutations and tumor antigens in both MCPyV-negative and MCPyV-positive MCCs were identified.

  Study phs002515

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Study EGAS00001002891

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Study EGAS00001002892

• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• Privacy Notice for EGA Web user

  Privacy Notice for EGA Public Website This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at: mfreeberg@ebi.ac.uk , or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? For providing you access to the website and for offering support whilst using the website, we need your consent under Article 5 (2) of the IP 68 (equivalent to Article 6 (1)(a) of the GDPR). For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: IP addressesDate and time of a visit to the service website Operating systemAmount of data transmittedBrowserEmail address (only when support is requested by the user) The data controller will use your personal data for the following purposes: To provide the user access to the serviceTo better understand the needs of the users and guide future improvements of the serviceTo monitor website activities according to and in compliance with the Terms of UseTo better understand the needs of the website visitors and guide future improvements of the serviceTo conduct and monitor website security activitiesTo create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organisations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you.Object at any time to the processing of your personal data unless we can demonstrate that we have legitimate reasons to process your personal data.Request free of charge and without excessive delay rectification or erasure of your personal data if we have not been processing it respecting the data protection policies of the respective controllers. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. 9. CookiesWe use cookies and similar technologies that are strictly necessary for the correct functioning and security of the EGA website (for example, to enable core site features and to help protect the service). These cookies do not store information that directly identifies you.You can set your browser to block or delete cookies. Please note that if you disable strictly necessary cookies, parts of the website may not function properly.Published on February 6, 2019

  Documentation data-protection/privacy-notice/ega-website

• Prostate_Cancer_Whole_Genome_Validations

  We propose to definitively characterise the somatic genetics of Prostate cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. This study will aim to validate the findings of the whole genome study by re-sequencing regions of interest using a bespoke pulldown bait. See ICGC website for more information: http://icgc.org/icgc/cgp/70/508/71331

  Study EGAS00001000427

• A Dose Escalation Study of Efmarodocokin Alfa (UTTR1147A) in Healthy Volunteers and Patients with Ulcerative Colitis

  Background: The interleukin-22 cytokine (IL-22) has demonstrated efficacy in nonclinical colitis models with a non-immunosuppressive mechanism-of-action. Efmarodocokin alfa (UTTR1147A) is a fusion protein agonist that links IL-22 to the crystallizable fragment (Fc) of human immunoglobulin (IgG4) for improved pharmacokinetic characteristics, but with a mutation to minimize Fc effector functions. Methods: This randomized, phase 1b study evaluated the safety, tolerability, pharmacokinetics, and pharmacodynamics of repeat intravenous dosing of efmarodocokin alfa in healthy volunteers (HVs; n=32) and patients with ulcerative colitis (UC; n=24) at 30–90 µg/kg doses given biweekly (Q2W) or monthly (Q4W) (6:2 active:placebo per cohort). Results: The most common adverse events (AEs) were on-target dermatological effects (dry skin, erythema, and pruritus) that were reversible. Dose-limiting non-serious dermatological AEs (severe dry skin, erythema, exfoliation, and discomfort) were seen in two HVs and one patient at 90 ug/kg Q2W. Pharmacokinetics were generally dose-proportional across the dose levels tested, but patients demonstrated lower drug exposures relative to HVs at the same dose. IL-22 serum biomarkers and IL-22 responsive genes in colon biopsies were induced with active treatment. Patients demonstrated changes in microbiota composition following active treatment, thereby reversing baseline dysbiosis. Clinical response was observed in 7/18 active- and 1/6 placebo-treated patients; clinical remission was observed in 5/18 active- and 0/6 placebo-treated patients.

  Study EGAS00001006172

• Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model including 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX NOD-scid IL2Rgnull mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either R-CHOP, huCD20-Fc-AFN-CHOP, or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the SMARTer Stranded Total RNA-seq pico v3 kit.

  Study EGAS50000000566

• High titers and low fucosylation of early phase anti-SARS-CoV-2 IgG promote hyper-inflammation by alveolar macrophages

  We show that early phase anti-Spike IgG in serum of critically ill COVID-19 patients induces hyper-inflammatory responses by human alveolar macrophages. We identified that this excessive inflammatory response is dependent on two antibody features that are specific for severe COVID-19. First, inflammation is driven by high titers of anti-Spike IgG, a hallmark of severe disease. Second, we found that anti-Spike IgG from severely ill patients is intrinsically more pro-inflammatory because of different glycosylation of the Fc tail, particularly by low fucosylation. This dataset is linked with the following ArrayExpress Experiment: E-MTAB-10431 - 2020_COVID19_FCGR_MIL10_IgGfucosylation

  Study EGAS00001005206

• Legal Notice EGA is a joint effort by the EBI and CRG. Please, check their terms of use and legal notice in order to follow them in the usage of the EGA website. EBI terms of use CRG terms of use

  Documentation legal-notice

• dataset1

  Contains test sample 1-26

  Dataset EGAD00010002041

• New set of services for all users unveiled at the EGA

  The European Genome-phenome Archive (EGA) releases today a brand-new website as well as a set of improved services for users, comprising a revamped Submitter Portal with an improved API and data brokering functionality for submitters, as well as a new DAC Portal for Data Access Committee members to easily manage data access requests. The EGA team has been working hard over the past months on these improvements that will provide a better experience for the users. Discover them below! Visit our new EGA website and check the new functionalities and updated guides Our new website is live, with a fresh look and updated features to discover all the novelties. The homepage now includes three pathways to guide our users, depending on whether they want to deposit, download or manage data within the Archive. One of the most outstanding developments is the introduction of a streamlined process for requesting access to data: EGA Users can now directly request access to their preferred datasets through the website using their EGA accounts. Additionally, users can customise their profile, oversee active sessions, and manage the public keys, essential for our latest array of services, alongside a range of other features. Another major change is our new Help Desk contact method: a built-in website form tailored for user inquiries. This system, called "Need Help?", can be easily located on the top right-hand side of the website. It will encompass both EGA and Federated EGA node users' requests. We will detail its use soon, so stay tuned. Register your metadata to the EGA easily with our new Submitter Portal The new Submitter Portal makes the submission process quicker and more intuitive. The process is currently divided into sections that the user will know beforehand by taking the tour that the EGA team has created to guide users through the Portal before starting the first submission. Do not complete your data submissions alone! Our Submitter Portal now includes a collaboration mode so that every submission can be completed by authorised collaborators with an EGA Profile. There are a lot more features that we will be detailing from now on in incoming posts. A new platform for Data Access Committee Members The new DAC Portal brings novelties for individuals engaged in governance, legal, technical, operational roles, or those acting as data stewards. DAC members will be able to easily manage DACs, policies, and data access requests with the new Portal. Take the tour now to check them out! Help us improve the services completing the EGA Survey As part of our ongoing journey to improve your experience, we have created an EGA User Survey. This questionnaire covers a wide range of aspects such as user experience, support and data accessibility, among others. Participate now and take the opportunity to suggest your own improvements. Help us enhance your experience in this new era for the EGA. Subscribe to the EGA Mailing List and stay tuned In the next weeks we will share more information about the possibilities of the new services. You can easily join the EGA Mailing List to receive all the updates.

  Blog new-set-of-services-at-EGA

• DAC-2020-03-26-Lemola (DAC-039))

  DAC-2020-03-26-Lemola (DAC-039)), raw data in EGA, metadata in Harvard Dataverse

  Dataset EGAD50000000897

• T cell transcriptional gradient

  There are two datasets: 1. scRNA-seq of human cutaneous immune cells from psoriasis patients. These include pre- and post-Tildrakizumab treated patients and come in a BAM file format. 19006FL-25-01 19006FL-38-01 19006FL-32-01-03 19006FL-33-01 19006FL-28-01-05 19006FL-35-01-01 2. RNA-seq of ZFP36L2 CRISPIR deleted Human T cells are FASTQ files. 19006XR-30-05 19006XR-30-04 19006XR-30-02 19006XR-30-01 19006XR-26-05 19006XR-26-04 19006XR-26-02 19006XR-26-01 19006R-22-04 19006R-22-08 19006R-22-05 19006R-22-01

  Dataset EGAD00001009677

• WGS of Multiple Myeloma/MGUS/SMM cases (germline) - VCF files (SNPs)

  WGS - PCR-free library preparation (whole blood gDNA), paired-end (2x100bp) sequencing on DNBseq sequencing platform (BGI) Number of samples: 26

  Dataset EGAD50000001800

• ATAC-seq

  ATAC-seq data for 26 CLL samples (7 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005967

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: kidney (2019-03-26)

  This dataset contains all the data available for this study on 2019-03-26.

  Dataset EGAD00001004867

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• Epigenomics Studies in Acute Myeloid Leukemia (AML)

  Acute Myeloid Leukemia (AML) remains a clinical challenge since most patients diagnosed with AML will die from the disease. Some patients harbor treatment-refractory disease and many others relapse with disease that in many cases is resistant to treatments. Our study was designed to understand the molecular basis of disease progression in AML through assessing genomics signatures in patient specimens collected through an international collaboration which assembled samples from 138 AML patients which experienced disease relapse and normal hematopoietic cells (n=15). It is hoped that this resource will help researchers understand mechanisms of disease relapse in AML and contribute to the general pool of data available for analyses for this disease and general research use.

  Study phs001027

• Coenzyme Q10 (CoQ) in Huntington's Disease (HD) (2CARE)

  This is a multi-center, randomized, double-blind, placebo-controlled trial of CoQ involving 609 ambulatory subjects with HD who are not requiring skilled care or institutionalization. Eligible subjects were randomized to receive either CoQ 2400 mg/day or matching placebo. Subjects were followed prospectively and systematically for 60 months of double-blind observation. The primary outcome variable is a combination of time to death (for subjects who die) and the change from baseline to Month 60 in Total Functional Capacity (TFC) score (for subjects who survive). The primary hypothesis of the study is that chronic treatment of early-stage HD subjects with high-dosage CoQ will slow the progressive functional decline of HD.

  Study phs001065

• H3Africa H3AChipDesign TrypanoGEN1

  26 samples from Cameroon generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004393

• Characterization of a New Case of XMLV (Bxv1) Contamination in the Human Cell Line Hep2 (Clone 2B) Using High-Throughput DNA- and RNA-Seq

  We have sequenced DNA and RNA from the Hep2 (clone 2B) cell line (Sigma-Aldrich catalog number: 85011412-1VL) using short read Illumina sequencing. We show that this cell line is indistinguishable from the HeLa cell line (as mentioned on the Sigma-Aldrich website) by mapping integrations of the human papillomavirus 18. We also show that the cell line is contaminated by the Bxv1 xenotropic murine leukemia virus. This contamination has to be taken into account when using the cell line in future experiments.

  Study phs001944

• Woodcock et al TenMenDeep Study EGA Dataset B

  Woodcock et al TenMenDeep EGA Dataset B. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005382

• Woodcock et al TenMenDeep Study EGA Dataset A

  Woodcock et al TenMenDeep EGA Dataset A. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005381

• Refractory Classic Hodgkins Lymphoma (cHL) sWGS

  Associated with the study: Blood-based Monitoring of Relapsed/Refractory Hodgkin Lymphoma Patients Predict Responses to Anti-PD-1 Treatment. 26 ctDNA Samples from 4 patients followed longitudinally. sWGS performed for copy number aberration (CNA) analysis.

  Dataset EGAD50000001163

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  DAC for RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  Dac EGAC50000000627

• Comprehensive genetic analysis of uveal melanoma heterogeneity during metastatic progression

  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Despite improvement of diagnosis and treatment of the primary tumor, there is no effective treatment of metastatic disease and approximately half of patients will die within one year or less following metastases detection. Tumor heterogeneity has been proposed as a key factor of drug resistance. However, it has been scarcely studied in UM. The present project aims searching for specific drivers of the metastatic progression, describing the genomic and transcriptomic landscape of metastatic UM, exploring tumor heterogeneity and investigating its role in drug resistance. Thus whole exome sequencing and transcriptomics have been performed on constitutional, primary tumor and metastatic samples from 28 UM patients.

  Study EGAS00001002761

• WGS_of_healhy_mesothelial_cells_and_primary_mesothelima_cell_lines

  Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, here we aim at performing WGS of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

  Study EGAS00001005559

• Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

  Gene expression profiles of single cells from 26 chemo-naïve and IDS tumor tissue and ascites samples from 17 HGSC patients

  Study EGAS50000000607

• dataset1

  Contains 14 control samples and 26 case samples.

  Dataset EGAD00001008576

• Prostate Cancer Whole Genome Validations

  We propose to definitively characterise the somatic genetics of Prostate cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. This study will aim to validate the findings of the whole genome study by re-sequencing regions of interest using a bespoke pulldown bait. See ICGC website for more information: http://icgc.org/icgc/cgp/70/508/71331

  Dataset EGAD00001000621

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001513

• Sequencing files for "Transcriptional Mechanisms of Resistance to Anti-PD-1 Therapy"

  Files from whole exome sequencing of 26 tumors and two matched normals from one melanoma patient. The 26 tumors include the untreated primary, cutaneous metastases and distant metastases to internal organs.

  Dataset EGAD00001003200

• Evolutionary Origins of Recurrent Pancreatic Cancer

  Surgery is the only curative option for patients with Stage I/II pancreatic cancer, nonetheless most patients will recur after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer we performed whole exome or targeted sequencing of 10 resected primary cancers and their matched intrapancreatic recurrences or distant metastases. We identified that recurrent disease develops from a monophyletic or polyphyletic origin, and this distinction has potential clinical relevance. In all patients, treatment induced genetic bottlenecks led to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In one patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings strongly advocate for routine post-treatment sampling in the management of recurrent pancreatic cancer.

  Study EGAS00001004097

• Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

  A dataset of ER+PR+ breast tumor samples that were analyzed in order to identify mutation enrichment in cis-regulatory elements and cistrome. The repository includes sequencing data from 88 patients. 26/88 were sequenced using ATAC-seq

  Dataset EGAD00001007650

• Phenotype information

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model in-cluding 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincris-tine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with CHOP (huCD20-Fc-AFN-CHOP), or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the using the SMARTer Stranded Total RNA-Seq Kit v3.

  Dataset EGAD50000000806

• Long-read data (PacBio)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006597

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Drug Perturbation of Primary Lymphoma Patient Samples and RNA Sequencing

  This submission contains 3'-end-based shallow-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule drugs (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). The samples were sequenced after 48 hours. The total data set consists of 1476 RNA sequencing samples from 6 batches (pilot, batch 1, batch 1 replicate, batch 2, batch 3, batch 4).

  Study EGAS50000001500

• Lymphoma_primary_patient_drug_perturbed_RNASeq_samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET-762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dac EGAC50000000578

• Pancreatic Cancer Case Control Association Study

  Pancreatic cancer is the fourth leading cause of cancer death in the United States. This is in large part due to the rapidly fatal course of this disease, as the vast majority of patients die within months of diagnosis and the five-year survival rate is less than 5. We have brought together over 8000 participants from 9 studies of pancreatic cancer, to conduct a GWAS of pancreatic cancer. The studies were drawn from the Pancreatic Cancer Case-Control consortium and include case-control studies from the United States, Europe and Australia. Sites include: Johns Hopkins National Familial Pancreas Tumor Registry, Mayo Clinic Biospecimen Resource for Pancreas Research, Ontario Pancreas Cancer Study (OPCS), Yale University, MD Anderson Case Control Study, Queensland Pancreatic Cancer Study, University of California San Francisco Molecular Epidemiology of Pancreatic Cancer Study, International Agency of Cancer Research and Memorial Sloan Kettering Cancer Center.

  Study phs000648

• RNAseq_of_healthy_mesothelial_cells_and_primary_mesothelioma_cell_lines

  Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, including anti-angiogenic therapies, immunotherapy, antibody-drug conjugates and oncolytic viruses, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, in this project we aim at performing a comprehensive transcriptomic analysis of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

  Study EGAS00001005728

• scMultiome (snRNA + snATAC) data of 26 regionally sampled GBM tissue from 6 patients

  This dataset contains snRNA-seq data of 26 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed unsorted or by sorting with 7AAD to remove debris and dead cells. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit, nuclei were barcoded and RNA and ATAC libraries were constructed, allowing for simultaneous capture of transcriptome and epigenome from the same cells.

  Dataset EGAD50000001838

• Exome-sequencing of human B cell lymphoma cell lines

  26 cell lines derived from human Diffuse Large B Cell lymphomas (DLBCL) or Burkit Lymphomas (BL) were subjected to whole exome sequencing. Exome capture was carried out using the SeqCap EZ Exome Library 2.0 kit (Roche/Nimblegen) and 100 bp single-read sequencing was performed on a HiSeq2500 (Illumina). 82% of the coding region was covered at least 30x.

  Dataset EGAD00001002262

• Whole Exome Sequencing of gliomas

  Dataset EGAD00001001614

• WES in muscle-invasive bladder cancer (MIBC) treated with durvalumab plus olaparib in the neoadjuvant setting: NEODURVARIB trial

  This submission contains the metadata derived from the whole exome sequencing of 70 samples from 26 patients who developed advanced urothelial carcinomas. The patients were enrolled in the Neodurvarib clinical trial, which compares the molecular profiles at diagnosis and after neoadjuvant treatment with Durvalumab and Olaparib. In this regard, the analyzed samples include: normal tissue and tumoral tissue obtained from the transurethral resection of the bladder (TURBT, a procedure performed prior to neoadjuvant therapy) from the 26 patients (52 samples), as well as tissue obtained from the radical cystectomy (a procedure performed after treatment with the aforementioned drugs; 18 samples).

  Study EGAS50000000791

• InsPIRE islets

  We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

  Study EGAS00001003997

• Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

  We performed genetic analysis of HLA and immune escape genes in samples from 44 patients sequenced by whole exome sequencing (34 tumor samples, 32 normal samples) and whole genome sequencing (10 tumor samples, 12 normal samples). We also performed HLA targeted sequencing in 26/44 patients (26 tumor samples, 26 normal samples).

  Dataset EGAD00001007565

• Bladder cancer sequencing data

  Dataset EGAD00001001036

• WGS Fastq files from the CPC-Gene project in support of PRAD-CA, DCC Release 26

  PRAD-CA, DCC Release 26 : This dataset contains fastq files with Whole genome sequencing data for the CPC-Gene Project. Data from each sample was generated using multiple whole genome libraries and sequenced across multiple runs

  Dataset EGAD00001003706

• Low-pass nanopore whole genome sequencing of brain tumors

  Dataset EGAD00001003382

• Meningioma Exome

  Meningioma Exome

  Dataset EGAD00001000099

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  Study on RNA-seq data from tumor tissue samples of primary tumors of advanced clear cell renal cell carcinoma patients enrolled in the NIVOREN GETUG-AFU-26 trial who consented to and participated in the translational program. The goal of this study was to assess previously published gene expression signatures and evaluate their association with the benefit and/or resistance to nivolumab, as well as their association with circulating soluble factors.

  Study EGAS50000001057

• RNA-seq after drug perturbation of primary lymphoma samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dataset EGAD50000002166

• Metastatic Prostate Follow Up 2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000989

• GWAS for Membranous Nephropathy

  Primary membranous nephropathy (MN) is a rare autoimmune cause of kidney failure. This dataset is from a genome-wide association study (GWAS) designed to identify novel genetic risk loci for MN. The provided cohort (named as European-1 Cohort) is composed of 611 cases of primary MN and 1,246 healthy controls of European ancestry. This cohort was used in the GWAS meta-analysis, as described in the manuscript entitled "Genetic architecture of membranous nephropathy and its potential diagnostic implications" (Nature Communications 2020, in press).The genome-wide summary statistics, including trans-ethnic meta-analysis across 8 GWAS cohorts of European and East Asian ancestry and ethnicity specific meta-analyses, are freely available for download on the Kiryluk lab website: http://www.columbiamedicine.org/divisions/kiryluk/resources.php.

  Study phs001984

• CPC-GENE Prostate Cancer Heterogeneity Study

  Raw sequence data, fastq format

  Dataset EGAD00001002885

• Genome analysis of oesophageal cancer and Barrett's oesophagus

  The median survival of oesophageal cancer this year is only 13 to 19 months after diagnosis and more than 90% will die from their disease. Therefore better treatment options are needed. The likelihood of cure for early screen-detected cancers is much higher. Barrett's oesophagus is a pre-cancerous lesion associated with a 30-40 fold increased risk of developing cancer. In an attempt to detect cancer early many patients with Barrett's are enrolled into surveillance programs involving regular endoscopies. A major problem with this approach is that the prevalence of BO in the population is estimated to be around 2%, but most patients with BO will never develop cancer. We are undertaking genomic and/or transcriptomic analysis of oesophageal tumours, Barrett's oesophagus and matched normal samples. The aim is to identify oesophageal-related genomic and transcriptomic alterations, which may reveal mutational process occurring, suggest biomarkers of tumour progression and treatment and identify novel treatment strategies.

  Study EGAS00001002864

• Immunoprotective mechanisms and microbiota interplay in Salmonella Typhi infection

  Vaccine development against Salmonella enterica serovar Typhi (S. Typhi) requires a better understanding of interaction between human host and the resident microbial consortia in gastrointestinal tract. Healthy adult volunteers received either Ty21a, M01ZH09 or placebo, and underwent challenges with wt S. Typhi. Stool samples were collected at the screening interview (Baseline 1), prior to the first vaccination visit (Baseline 2), during vaccination (Day -28 and -26 for placebo and M01ZH09 groups; Day -32, -30, -28, -26 for Ty21a group), prior to challenge with S. Typhi (Day 0), and after challenge (day 0 12h, day 1, day 3, day 7, and day 10). 16S rRNA and messenger RNA were extracted from stool and sequenced on the Illumina Miseq and HiSeq 2000 platforms, respectively.

  Study phs001521

• CRLF2 sequencing project Exomes

  CRLF2 sequencing project Exomes

  Dataset EGAD00001000077

• Functional characterisation of CpG islands in human tissues

  Functional characterisation of CpG islands in human tissues

  Dataset EGAD00001000212

• WGS

  Whole Genome Sequencing

  Dataset EGAD00001001120

• All counts

  This dataset is the expression profiling by high throughput sequencing, including all counts of genes for all samples in two groups. It includes 26 samples totally (Lean healthy group includes 12 samples: s001/SR01_Bright, s002/SR01_Dim, s004/SR02_Bright, s005/SR04_Dim, s006/SR04_Bright, s007/SR05_Dim, s008/SR05_Bright, s009/SR06_Bright, s011/SR07_Dim, s012/SR07_Bright, s013/SR08_Bright, s014/SR08_Dim; DM2 group includes 14 samples: s015/SR201_Bright, s017/SR202_Bright, s018/SR202_Dim, s019/SR203_Bright, s020/SR203_Dim, s021/SR204_Bright, s022/SR204_Dim, s023/SR205_Dim, s025/SR206_Dim, s026/SR206_Bright, s027/SR207_Dim, s028/SR207_Bright, s029/SR208_Bright, s030/SR208_Dim). It is a TAB file.

  Dataset EGAD50000001715

• WES of melanoma tumors treated with combined immune checkpoint blockade

  This study of pre-treatment melanoma tumor samples from patients subsequently treated with combined anti-CTLA-4 and anti-PD-1 checkpoint blockade sought to identify genomic biomarkers of response to therapy. A total of 26 tumor and matched normal samples underwent whole exome sequencing.

  Study EGAS00001003857

• Single nucleus RNA Seq of LUAD patient derived lung samples

  Fastq files of single nucleus RNA Sequencing data from 26 patients including 26 lung adenocarcioma and 12 matched healthy tissue samples for 8 young female never smokers, 8 young female smokers, 7 elderly female never smokers and 3 male never smokers.

  Dataset EGAD00001008955

• Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.

  This dataset consists of shallow whole genome sequencing data and amplicon sequencing data for 26 ovarian cancer patients (21 high-grade serous ovarian cancer, 4 low-grade serous ovarian cancer and 1 clear cell ovarian cancer). The data are provided as single end FASTQ files for the shallow whole genome sequencing data (31 libraries) and paired end FASTQ files for the amplicon sequencing data (98 libraries).

  Dataset EGAD00001008716

• Sequencing data for oesophageal and related samples - ICGC DCC release 26 (WGS)

  WGS sequencing for 303 cases (620 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 26

  Dataset EGAD00001003580

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

  This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

  Dataset EGAD00001004823

• Anaplastic meingioma methylation

  Methylation of anaplastic meningiona samples

  Dataset EGAD00010001629

• Error-corrected sequencing of 26 driver genes

  387 swab samples were sequenced. The bam files contain consensus reads.

  Dataset EGAD50000000079

• WGS in insulinomas

  Whole-Genome Sequencing datasets of insulinoma samples and paired blood controls

  Dataset EGAD50000000464

• Comprehensive genetic analysis of uveal melanoma heterogeneity during metastatic progression

  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Despite improvement of diagnosis and treatment of the primary tumor, there is no effective treatment of metastatic disease and approximately half of patients will die within one year or less following metastases detection. Tumor heterogeneity has been proposed as a key factor of drug resistance. However, it has been scarcely studied in UM. The present project aims searching for specific drivers of the metastatic progression, describing the genomic and transcriptomic landscape of metastatic UM, exploring tumor heterogeneity and investigating its role in drug resistance. Thus whole exome sequencing and transcriptomics have been performed on constitutional, primary tumor and metastatic samples from 28 UM patients.

  Dataset EGAD00001004554

• Pancreatic adenocarcinoma QCMG 20110901

  Pancreatic adenocarcinoma QCMG 20110901

  Dataset EGAD00001000049

• Gut metagenomic data of 2,338 Pinggu adults

  Here we exploited a Han Chinese population-based cohort with extensive host metadata established in the Pinggu (PG) district of Beijing, and investigated gut microbiota from 2,338 adults (26-76 years) by metagenomic sequencing, revealing associations of the gut microbiota with sex, sex hormones, age, and a number of clinical and metabolic parameters.

  Study EGAS00001004820

• Error-corrected sequencing of 26 driver genes (additional cohort)

  An additional 320 swab samples were sequenced. The bam files contain consensus reads.

  Dataset EGAD50000000641

• RNAseq dataset

  RNAseq experiment after DIS3 ASO or Control ASO treatment on human cells under plasmablast differentiation.

  Dataset EGAD50000001243

• Whole Exome Sequencing

  Whole Exome Sequencing Data for 10 patients for treatment with the ICI Nivolumab

  Dataset EGAD00001011117

• Sequencing data for oesophageal and related samples - OACs release 2 (RNA)

  Dataset EGAD00001003839

• Exome reads and RNA-seq

  Exome sequencing for 26 patients with matched blood RNA-seq for 41 patients

  Dataset EGAD00001002722

• Prostate cancer datasets WES

  WES: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (HiSeq)

  Dataset EGAD00001004467

• RNAseq

  RNAseq was performed on CDX, CDX-derived cell line and LNCaP cell line, with triplicates.

  Dataset EGAD00001006008

• WES of der(1;7)(q10;p10) myeloid neoplasms

  The study examined WES of der(1;7)(q10;p10) myeloid neoplasm cases. BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10) were used to identify key driver genes in patients with der(1;7)(q10;p10). This study is one of the largest WES for der(1;7)(q10;p10)(+) myeloid neoplasm cases.

  Study EGAS50000000704

• Long-read and short-read isoform sequencing in breast cancer

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Study EGAS00001004819

• alopecia areata

  exome sequencing files from 25 alopecia areata samples from spain.

  Dataset EGAD00001006370

• UK Biobank whole cohort directly genotyped and imputed data (~500,000 participants)

  Genotype data is available for all 500,000 participants in the UK Biobank cohort. Genotyping has been performed using the Affymetrix UK BiLEVE Axiom array on an initial 50,000 participants and the remaining 450,000 participants have been genotyped using the Affymetrix UK Biobank Axiom® array. The two arrays are extremely similar (with over 95% common content).Quality control and imputation (to over 90 million SNPs, indels and large structural variants) has been performed by a collaborative group headed by the Wellcome Trust Centre for Human Genetics.The following data are available:* A clean set of QC’ed genotype calls* Confidence values that a genotype call is correct* Intensity data to generate cluster plots* Extensive QC information regarding SNPs and samples including SNP metrics, batch effects, population structure and relatedness* Imputed dataFor further information, please refer to the UK Biobank website

  Study EGAS00001002399

• Beacon v2

  Beacon v2: a tool for data discovery Motivation In the era of data-driven health research and personalised medicine, human genomic data has become extremely valuable. These are also identifiable data, as they carry information pointing to a specific individual as well as their own family; and as such, they must be protected. This makes data discovery particularly challenging: this is where “Beacon” comes in. A “Beacon” is an API aiming to enable the search of genomic variants and associated information without jeopardising the privacy of the dataset. Here, we refer to its current version, namely version 2 (v2). Definition Beacon v2 is a term that can refer to different aspects. The EGA is playing a central role in the following aspects: The Beacon v2 protocol is a Global Alliance for Health and Genomics standard. The Beacon v2 Reference Implementation (B2RI) is an “out-of-the-box” Beacon instance developed with ELIXIR, which facilitates Beacon deployment. The EGA Beacon(s) are Beacons following the v2 standard and using the B2RI, deployed on top of data hosted at the EGA and allowing for their discovery. Resources Depending on whether you are visiting us a stakeholder (you need more general information about Beacon), a deployer /implementer (you want to have your own Beacon instance), or an EGA user (you want to query Beacon and start browsing data), you will be interested in the following resources: Your role Beacon aspect Documentation type Stakeholder Beacon v2 protocol Beacon website Beacon page on the GA4GH website Deployer/Implementer Beacon v2 protocol Read the docs: Beacon v2 standard technical description GitHub repository Beacon v2 standard Beacon v2 Reference Implementation Read the docs: B2RI technical description GitHub repository B2RI Guide to deploy Beacon using B2RI EGA user EGA Beacon(s) API in construction UI in construction

  Documentation about/projects-and-funders/beacon

• RNAseq SCLC Cell lines MYC

  RNAseq data set (Mollaoglu et al., MYC drives progression of small cell lung cancer to a variant neuroendocrine subtype with vulnerability to Aurora kinase inhibition) RNA isolation from primary tumors and healthy lungs was performed using RNeasy Mini Kit (Qiagen) with the standard protocol. RNA was subjected to library construction with the Illumina TruSeq Stranded mRNA Sample Preparation Kit (cat# RS-122-2101, RS-122-2102) according to manufacturer’s protocol. Chemically denatured sequencing libraries (25 pM) are applied to an Illumina HiSeq v4 single read flow cell using an Illumina cBot. Hybridized molecules were clonally amplified and annealed to sequencing primers with reagents from an Illumina HiSeq SR Cluster Kit v4-cBot (GD-401-4001). Following transfer of the flowcell to an Illumina HiSeq 2500 instrument (HCSv2.2.38 and RTA v1.18.61), a 50 cycle single-read sequence run was performed using HiSeq SBS Kit v4 sequencing reagents (FC-401-4002).

  Dataset EGAD00001003099

• Prostate cancer datasets WGS

  Low pass WGS: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (Next Seq )

  Dataset EGAD00001004466